Macroscopic Gamma Oscillation With Bursting Neuron Model Under Stochastic Fluctuation
Macroscopic Gamma Oscillation With Bursting Neuron Model Under Stochastic Fluctuation
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随机涨落下的宏观伽玛振荡与爆发神经元模型
DOI：
10.1162/neco_a_01570
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发表时间：
2023
影响因子：
2.9
通讯作者：
Jimbo Yasuhiko
中科院分区：
文献类型：
--
作者：
Yoshikai Yuto;Zheng Tianyi;Kotani Kiyoshi;Jimbo Yasuhiko
伽马振荡被认为在大脑的信息处理中起着重要作用。爆发神经元，表现出周期性的簇状尖峰活动，是一种被认为对伽马振荡有很大贡献的神经元。然而，关于破裂神经元的特性如何影响伽马振荡的出现、波形和同步特性，特别是在随机波动下，我们知之甚少。在这项研究中，我们提出了一个可以分析爆发率和相位响应函数的爆发神经元模型。然后从理论上分析了由爆发性兴奋神经元和抑制性神经元混合组成的神经元群体动态。等效Fokker-Planck方程的分岔分析显示，在不同的相互作用强度下，存在单峰放电、抑制性群体的双峰放电和兴奋性群体的双峰放电三种类型的伽马振荡。利用Fokker-Planck方程的伴随方法分析宏观相响应函数，发现抑制双线有利于高频振荡的同步。在保持相互作用强度不变的情况下，降低单个神经元的爆发率会增加总体相耦合函数的相对高伽马分量。这也提高了神经元群体模型与更快的振荡输入同步的能力。本研究的分析框架提供了对爆发神经元种群的非平凡动力学的见解，进一步表明爆发神经元在节律活动中起重要作用。
Gamma oscillations are thought to play a role in information processing in the brain. Bursting neurons, which exhibit periodic clusters of spiking activity, are a type of neuron that are thought to contribute largely to gamma oscillations. However, little is known about how the properties of bursting neurons affect the emergence of gamma oscillation, its waveforms, and its synchronized characteristics, especially when subjected to stochastic fluctuations. In this study, we proposed a bursting neuron model that can analyze the bursting ratio and the phase response function. Then we theoretically analyzed the neuronal population dynamics composed of bursting excitatory neurons, mixed with inhibitory neurons. The bifurcation analysis of the equivalent Fokker-Planck equation exhibits three types of gamma oscillations of unimodal firing, bimodal firing in the inhibitory population, and bimodal firing in the excitatory population under different interaction strengths. The analyses of the macroscopic phase response function by the adjoint method of the Fokker-Planck equation revealed that the inhibitory doublet facilitates synchronization of the high-frequency oscillations. When we keep the strength of interactions constant, decreasing the bursting ratio of the individual neurons increases the relative high-gamma component of the populational phase-coupling functions. This also improves the ability of the neuronal population model to synchronize with faster oscillatory input. The analytical frameworks in this study provide insight into nontrivial dynamics of the population of bursting neurons, which further suggest that bursting neurons have an important role in rhythmic activities.